Deep Learning: A Practitioner's Approach

Patterson Consulting, a solution integrator at the convergence of big data and applied machine learning, is led by Josh Patterson. In this job, he contributes to Fortune 500 initiatives his unique perspective based on a decade of big data knowledge and broad deep learning experience.

Adam Gibson is a deep learning specialist based in San Francisco who creates machine learning projects for Fortune 500 corporations, hedge funds, public relations agencies, and startup accelerators. Adam has a proven track record of assisting businesses in handling and interpreting large amounts of real-time data.

Although there is a lot of interest in machine learning, unrealistic expectations often kill initiatives before they ever get started. How might machine learning, particularly deep neural networks, help your organization? Among the best books on deep learning, Deep Learning: A Practitioner's Approach not only contains the most practical information on the subject, but it also assists you in getting started with developing efficient deep learning networks.

Before providing their open-source Deeplearning4j (DL4J) toolkit for constructing production-class workflows, authors Adam Gibson and Josh Patterson provide theory on deep learning. You'll cover methods and tactics for training deep network architectures and performing deep learning workflows on Spark and Hadoop with DL4J using real-world applications.

• Dive into general machine learning principles as well as deep learning in particular.
• Discover how deep networks evolved from neural network basics.
• Investigate the key deep network architectures, such as Convolutional and Recurrent.
• Learn how to apply specific deep networks to the appropriate situation.
• Take a look at the basics of adjusting general neural networks and specialized deep network topologies.
• Use DataVec, DL4J's workflow tool, to apply vectorization algorithms to various data formats.
• Learn how to use DL4J on Spark and Hadoop natively.

Author: Josh Patterson and Adam Gibson

Link to buy: https://www.amazon.com/dp/1491914254

Ratings: 4.2 out of 5 stars (from 70 reviews)

Best Sellers Rank: #804,585 in Books

#458 in Data Mining (Books)

#487 in Data Modeling & Design (Books)

#616 in Database Storage & Design